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95 records · Page 6

The sensitivity of runoff generation to spatial snowpack uniformity in an alpine watershed: Green Lakes Valley, Niwot Ridge Long-Term Ecological Research station

Seasonal water storage in high-elevation alpine catchments are critical sources of water for mountainous regions like the western U.S. The spatial distribution of snow in these topographically complex catchments is primarily governed by orography, solar radiation, and wind redistribution. While the effect of solar shading is relatively consistent from year-to-year, the redistribution of snow due to wind is more variable–capable of producing snowpacks that have varying degrees of uniformity across these hydrologically-important catchments. A reasonable hypothesis is that a warmer climate will cause snowfall to become more dense (i.e. wetter and heavier), possibly leading to less wind redistribution and thus produce a more uniformly distributed snowpack across the landscape. In this study, we investigate the role of increasingly uniform spatial snowpack distributions on streamflow generation in the Green Lakes Valley Niwot Ridge Long Term Ecological Research station, within the headwaters of the Boulder Creek watershed in Colorado. A set of idealized hydrologic simulation experiments driven by reconstructed snowpacks spanning 2001–2014 show that more a more uniform spatial snowpack distribution leads to an earlier melt-out of31 days on average and tends to produce less total streamflow, with maximum decreases as large as 7.5%. Isolating the role of snowpack heterogeneity from melt-season precipitation, we find that snowpack uniformity reduces total streamflow by as much as 13.2%. Reductions in streamflow are largely explained by greater expo-sure to solar radiation in the uniformly distributed case relative to a more heterogeneous snowpack, with this exposure driving shifts towards earlier snowmelt and changes in soil water storage. Overall, we find that the runoff efficiency from shallower snowpacks is more sensitive to the effects of uniformity than deeper snowpacks, which has potential implications for a warming climate where shallower snowpacks and enhanced sensitivities may be present.

Alpine catchment↗

Development and Evaluation of Ensemble Consensus Precipitation Estimates over High Mountain Asia

Precipitation estimates are highly uncertain in complex regions such as High-Mountain Asia (HMA), where ground measurements are very difficult to obtain, and atmospheric dynamics poorly understood. Though gridded products derived from satellite-based observations and/or reanalysis can provide temporally and spatially distributed estimates of precipitation, there are significant inconsistencies in these products. As such, to date, there is little agreement in the community on the best and most accurate gridded precipitation product in HMA, which is likely area dependent because of HMA’s strong heterogeneities and complex orography. Targeting these gaps, this article presents the development of a consensus ensemble precipitation product using three gridded precipitation datasets (the Integrated Multi-satellitE Retrieals for Global Precipitation Measurement IMERG, the Climate Hazards group Infrared Precipitation with Stations CHIRPS, and the ECMWF Reanalysis ERA5) with a localized probability matched mean (LPM) approach. We evaluate the performance of the LPM estimate along with a simple ensemble mean (EM) estimate to overcome the differences and disparities of the three selected constituent products on long-term averages and trends in HMA. Our analysis demonstrates that LPM reduces the high biases embedded in the ensemble members and provides more realistic spatial patterns compared to EM. LPM is also a good alternative for merging data products with different spatio-temporal resolutions. By filtering disparities among the individual ensemble members, LPM overcomes the problem of a certain product performing well only in a particular area and provides a consensus estimate with plausible temporal trends.

Fadji Z Maina↗

U.S. IMERG Status

The U.S. Science Team’s Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) product provides estimates of surface precipitation rate and related information on a global 0.1° half-hour grid. It is run three times at increasingly longer latency and higher information input to serve different communities. This presentation will briefly summarize the major upgrades included in Version 07. The Goddard Profiling (GPROF) algorithm (applied to passive microwave sensor data from the GPM virtual constellation) and the Combined Radar-Radiometer Algorithm (CORRA) that provide input to IMERG V07 are both improved, and the new Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Dynamic Infrared Rain Rate (PDIR) algorithm is being applied to infrared data, which employs an additional, warmer infrared temperature threshold than the previous infrared scheme and a deep neural network. V07 has improved bias performance as a result of calibrations that now employ the entire swath widths of CORRA and GPROF GPM Microwave Imager precipitation estimates. As well, time continuity in precipitation features is improved as a result of changes to the Kalman filter that approximately preserve the local histogram of precipitation rates (Scheme for Histogram Adjustment with Ranked Precipitation Estimates in the Neighborhood, or SHARPEN), and that better account for differences in sensor performance. A long-standing bug in the geolocation that shifted grid values 0.1° to the east in the latitude band 70°N-S has been corrected. Other changes in V07 include a hierarchical selection among motion vector sources to address deficiencies in the precipitation propagation near orography, an update to the precipitation phase specification for improved consistency with current inputs, and a renewed effort to implement climatological gauge adjustment to the near-real-time Runs. Early evaluations of V07 IMERG show interesting behavior across the TRMM orbit boost that is highly relevant to the planned orbit boost for the GPM Core observatory.

GPM↗

Mountain Waves in the Middle Atmosphere: Microwave Limb Sounder Observations and Analyses

Observations and analyses of mesoscale gravity waves in the stratosphere from the Upper Atmosphere Research Satellite (UARS) Microwave Limb Sounder (MLS) are summarized, with focus on global distribution of topography related wave activities. We found most of the orographical wave activities occur during the winter seasons over high latitude mountain ridges. In the northern hemisphere, the strongest waves are those over Scandinavia, Central Eurasia, and southern Greenland, whereas in the southern hemisphere, wave activities are outstanding over the Andes, New Zealand, and Antarctic rim;, MLS observations suggest that these orographic waves are located mostly on the down stream side of the mountain ridge with downward phase progression and have horizontal phase velocities opposite to the stratospheric jet-stream. Future studies using MLS data and numerical modeling will lead to better understanding of gravity wave effects on dynamics and chemistry in the middle atmosphere.

UPPER ATMOSPHERE↗